AI Cooking Device Vibration Detection for Boiling State Determination
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Solution Overview
Problem
Existing cooking devices require multiple sensors and complex logic to determine if ingredients are boiling, which can lead to inaccuracies and user inconvenience, especially when external noise or changes in ingredient conditions occur.
Innovation Solution
An artificial intelligence cooking device that uses a vibration sensor to detect the vibration signal of ingredients and inputs this data into an AI model to determine if they are boiling, simplifying the processing algorithm and improving accuracy by considering only current data without chronological analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors and complex logic are used to determine boiling, then measurement coverage is improved, but device complexity increases and measurement precision decreases
Solution Approach 1:
The patent extracts and focuses on the most critical feature for boiling detection - vibration characteristics - while eliminating the need for multiple sensors. By using only a vibration sensor to capture acceleration data in three axes, the system achieves accurate boiling determination without the complexity of combining data from vibration sensors, infrared sensors, weight sensors, sound wave sensors, photo sensors, timers, acoustic sensors, optical sensors, and temperature sensors as proposed in prior art.
Solution Approach 2:
The patent replaces complex mechanical and logical processing systems with an artificial intelligence model. Instead of using complex logic to process and combine data from multiple sensors, the system uses a trained AI model that automatically analyzes vibration characteristics and determines boiling state, significantly simplifying the system while improving accuracy.
2Device complexity
If chronological-order logic is used to analyze vibration signals, then processing structure is simplified, but measurement precision decreases due to misjudgment under limited conditions
Solution Approach 1:
The patent changes the approach from chronological-order analysis to AI-based parameter analysis. Instead of analyzing vibration signals in chronological order to detect boiling, the system uses a vibration sensor to capture acceleration data, which is then input to a trained AI model. The AI model analyzes vibration characteristics (frequency, amplitude, pattern) directly without being constrained by chronological flow, enabling accurate boiling determination even when external noise is present or cooking conditions vary.
Solution Approach 2:
The patent uses a trained AI model that has learned the characteristics of boiling vibrations from training data. The model copies the knowledge of boiling patterns acquired during training and applies it to real-time detection, allowing accurate boiling determination without being limited by chronological-order logic or specific cooking conditions.
3Ease of operation
If standardized chronological-order logic is used for boiling detection, then ease of operation is improved, but reliability decreases when external noise or condition changes occur
Solution Approach 1:
The patent implements a self-adaptive system using AI that automatically adjusts to different cooking conditions without requiring standardized logic. The trained AI model self-service by autonomously analyzing vibration characteristics and determining boiling state, making the system reliable under various conditions including external noise, different ingredient types, different cooking vessel types, and different ingredient amounts.
Solution Approach 2:
The patent creates a universal boiling detection system using AI that can handle multiple cooking scenarios. The trained AI model provides multi-functionality by accurately detecting boiling regardless of ingredient type, cooking vessel type, ingredient amount, or presence of external noise, eliminating the need for condition-specific logic while maintaining high reliability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The AI model accurately determines if ingredients are boiling, reducing the likelihood of misjudgment and user inconvenience, while allowing for various cooking schemes with minimal sensor interference from external noise, thus preventing overflow or fire.
Implementation Method 1
a vibration sensor for detecting a vibration signal of the ingredients in the cooking vessel
Data Source
AI summary
An artificial intelligence cooking device includes a plate including a heater configured to heat ingredients in a cooking vessel placed on the plate; a vibration sensor disposed below the plate configured to detect a vibration signal of the ingredients in the cooking vessel transmitted through the plate; and a processor configured to determine, via an artificial intelligence model having learned properties of the vibration signal, whether or not the ingredients in the cooking vessel are boiling based on the detected vibration signal provided to the artificial intelligence model and the learned properties of the vibration signal; and output information indicating whether or not the ingredients are boiling based on the determination.